Universiti Teknologi Malaysia Institutional Repository

Finger vein identification based on maximum curvature directional feature extraction

Yahaya, Yuhanim Hani and Shamsuddin, Siti Mariyam and Wong, Yee Leng (2019) Finger vein identification based on maximum curvature directional feature extraction. Journal of Creative Practices in Language Learning and Teaching (CPLT) Special Issue: Generating New Knowledge through Best Practices in Computing and Mathematical Sciences, 7 (1). pp. 42-48. ISSN 1823-464X

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Official URL: http://ir.uitm.edu.my/id/eprint/30605/

Abstract

Finger vein identification has become an important area of study especially in the field of biometric identification and has further potential in the field of forensics. The finger vein pattern has highly discriminative features that exhibit universality, uniqueness and permanence characteristics. Finger vein identification requires living body identification, which means that only vein in living finger can be captured and used for identification. Acquiring useful features from finger vein in order to reflect the identity of an individual is the main issues for identification. This research aims at improving the scheme of finger vein identification take advantage of the proposed feature extraction, which is Maximum Curvature Directional Feature (MCDF). Experimental results based on two public databases, SDUMLA-HMT datasets and PKU datasets show high performance of the proposed scheme in comparison with state-of-the art methods. The proposed approach scored 0.001637 of equal error rate (EER) for SDUMLAHMT dataset and 0.00431 of equal error rate for PKU dataset.

Item Type:Article
Uncontrolled Keywords:Finger Vein Identification, Maximum Curvature, Directional Feature
Subjects:Q Science > QM Human anatomy
Divisions:Chemical Engineering
ID Code:88217
Deposited By: Siti Norlela Isnin
Deposited On:15 Dec 2020 10:50
Last Modified:09 Feb 2021 01:45

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